Linear model for the scattered radiation distribution in digital chest radiographs

1996 ◽  
Author(s):  
Christiaan M. Fivez ◽  
Patrick Wambacq ◽  
Paul Suetens ◽  
Emile P. Schoeters
Keyword(s):  
Linear Model ◽  
Scattered Radiation ◽  
Chest Radiographs ◽  
Radiation Distribution ◽  
Digital Chest

Efficacy of Inverted Digital Luminescence Radiography in Evaluating Chest Neoplasms

1991 ◽  
Vol 32 (6) ◽  
pp. 442-448 ◽  
Author(s):  
M. Kehler ◽  
U. Albrechtsson ◽  
A. Andrésdóttir ◽  
P. Hochbergs ◽  
H. Lárusdóttir ◽  
...  
Keyword(s):  
Statistical Difference ◽  
Digital Images ◽  
Left Lung ◽  
Roc Curves ◽  
Lung Tumors ◽  
Chest Radiographs ◽  
Contrast Enhanced ◽  
Different Types ◽  
Digital Chest ◽  
Digital Luminescence Radiography

Inverted (positive) digital chest radiographs of patients with lung tumors were compared with commonly used (negative) digital images, consisting of one simulated normal and one contrast enhanced image. The first part of the material consisted of 80 patients of whom 40 had tumors and 40 were normal. Five radiologists with different experience reviewed the examinations. From their answers, ROC curves were constructed. The second part of the material consisted of 100 chest phantom examinations with a simulated tumor in the mediastinum (45 examinations) and/or the left lung (46 examinations). In 31 exposures there was no abnormality. These were reviewed by 3 observers and performed as an ROC study as well. There was no statistical difference between the different types of images or between the observers in the 2 studies.

Novel statistical analysis of two sources of digital chest radiographs

1996 ◽  
Author(s):  
Jacob K. Laading ◽  
Valen E. Johnson ◽  
Alan H. Baydush ◽  
Carey E. Floyd, Jr.
Keyword(s):  
Statistical Analysis ◽  
Chest Radiographs ◽  
Digital Chest

Automated selection of regions of interest for quantitative analysis of lung textures in digital chest radiographs

1993 ◽  
Vol 20 (4) ◽  
pp. 975-982 ◽  
Author(s):  
Xuan Chen ◽  
Kunio Doi ◽  
Shigehiko Katsuragawa ◽  
Heber MacMahon
Keyword(s):  
Quantitative Analysis ◽  
Regions Of Interest ◽  
Chest Radiographs ◽  
Digital Chest ◽  
Selection Of

Computer-Simulated Lung Nodules in Digital Chest Radiographs for Detection Studies

1990 ◽  
Vol 25 (8) ◽  
pp. 902-907 ◽  
Author(s):  
DAVID A. YOCKY ◽  
GEORGE W. SEELEY ◽  
THERON W. OVITT ◽  
HANS ROEHRIG ◽  
WILLIAM J. DALLAS
Keyword(s):  
Chest Radiographs ◽  
Lung Nodules ◽  
Digital Chest

ROC Analysis of Detection of Metastatic Pulmonary Nodules on Digital Chest Radiographs with Temporal Subtraction

2001 ◽  
Vol 8 (9) ◽  
pp. 871-878 ◽  
Author(s):  
Toshimi Uozumi ◽  
Katsumi Nakamura ◽  
Hideyuki Watanabe ◽  
Hajime Nakata ◽  
Shigehiko Katsuragawa ◽  
...  
Keyword(s):  
Roc Analysis ◽  
Pulmonary Nodules ◽  
Chest Radiographs ◽  
Temporal Subtraction ◽  
Digital Chest

scholarly journals A Computer-Aided Detection System for Digital Chest Radiographs

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Juan Manuel Carrillo-de-Gea ◽  
Ginés García-Mateos ◽  
José Luis Fernández-Alemán ◽  
José Luis Hernández-Hernández
Keyword(s):  
Template Matching ◽  
Detection System ◽  
Local Binary Patterns ◽  
Chest Radiographs ◽  
Computer Aided Detection ◽  
Success Rates ◽  
Novel Approach ◽  
Computer Aided ◽  
Digital Chest ◽  
Areas Of Interest

Computer-aided detection systems aim at the automatic detection of diseases using different medical imaging modalities. In this paper, a novel approach to detecting normality/pathology in digital chest radiographs is proposed. The problem tackled is complicated since it is not focused on particular diseases but anything that differs from what is considered as normality. First, the areas of interest of the chest are found using template matching on the images. Then, a texture descriptor called local binary patterns (LBP) is computed for those areas. After that, LBP histograms are applied in a classifier algorithm, which produces the final normality/pathology decision. Our experimental results show the feasibility of the proposal, with success rates above 87% in the best cases. Moreover, our technique is able to locate the possible areas of pathology in nonnormal radiographs. Strengths and limitations of the proposed approach are described in the Conclusions.

Comparison of Radiologist and CAD Performance in the Detection of CT-confirmed Subtle Pulmonary Nodules on Digital Chest Radiographs

2008 ◽  
Vol 43 (6) ◽  
pp. 343-348 ◽  
Author(s):  
Thorsten Alexander Bley ◽  
Tobias Baumann ◽  
Ulrich Saueressig ◽  
Gregor Pache ◽  
Markus Treier ◽  
...  
Keyword(s):  
Pulmonary Nodules ◽  
Chest Radiographs ◽  
Digital Chest
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